The Mule goes SURFing

A month ago I posted about “SURF”, the newly-established Sydney R user forum (R being an excellent open-source statistics tool). Shortly after publishing that post, I attended the inaugural forum meeting.

While we waited for attendees to arrive, a few people introduced themselves, explaining why they were interested in R and how much experience they had with the system. I was surprised at the diversity of backgrounds represented: there was someone from the department of immigration, a few from various areas within the health-care industry, a group from the Australian Copyright Council (I think I’ve got that right—it was certainly something to do with copyright), a few from finance, some academics and even someone from the office of state revenue.

Of the 30 or so people who came to the meeting, many classed themselves as beginners when it came to R (although most had experience with other systems, such as SAS). So if there’s anyone out there who was toying with the idea of signing up but hesitated out of concern that they know nothing about R, do not fear. You will not be alone.

The forum organizer, Eugene Dubossarsky, proceeded to give an overview of the recent growth in R’s popularity and also gave a live demo of how quickly and easily you can get R installed and running. Since there were so many beginners, Eugene suggested that a few of the more experienced users could act as mentors to those interested in learning more about R. As someone who has used R for over 10 years, I volunteered my services. So feel free to ask me any and all of your R questions!

As well as being a volunteer mentor, I will have the pleasure of being the presenter at the next forum meeting on the 18th of August. Regular readers of the Stubborn Mule will not be surprised to learn that the topic I have chosen is The Power of Graphics in R. Here’s the overview of what I will be talking about:

In addition to its statistical computing prowess, R is one of the most sophisticated and flexible tools around for visualizing quantitative data. It can produce a wide variety of chart types, including scatter plots, box plots, dot plots, mosaic plots, 3D charts and more. Tweaking chart settings and adding customized annotations is a breeze and the charts can readily be output to a range of formats including images (jpeg or png), PDF and metafile formats.

Topics covered in this talk include:

• Getting started with graphing in R
• The basic charting types available
• Customising charts (labels, axes, colour, annotations and more)
• Managing different output formats
• A look at the more advanced charting packages: lattice and ggplot2

Anyone who ever has a need to visualize their data, whether simply for exploration or for producing slick graphics for reports and presentations can benefit from learning to use R’s graphics features. The material presented here will get you well on your way. If you have ever been frustrated when trying to get charts in Excel to behave themselves, you will never look back once you switch to R.

For those of you in Sydney who are interested in a glimpse of how I use R to produce the charts you see here on the blog, feel free to come along. I hope to see you there!